基于视觉感知+蚁群算法的管道检测机器人避障研究  

Study of Obstacle Avoidance in Pipeline Inspection Robots Based onVisual Perception and Ant Colony Algorithm

作　　者：刘思默[1] LIU Simo(Institute of Intelligent Manufacturing,Fujian Institute of Information Technology,Fuzhou 350003,China)

机构地区：[1]福建信息职业技术学院智能制造学院,福建福州350003

出　　处：《兰州石化职业技术大学学报》2025年第1期37-42,共6页Journal of Lanzhou Petrochemical University of Vocational Technology

摘　　要：为了确保管道的安全运行,需要采用有效的检测方法和手段,以发现和评估管道的缺陷和损伤。目前,管道机器人是管道检测最有效的手段,然而在检测过程中会面临各种障碍物(缺陷)的影响,进而降低检测效率。鉴于此,在分析管道内机器人运动特性的基础上,提出了基于蚁群算法和双目视觉的管道机器人避障策略。利用双目视觉进行障碍物快速三维重建,有效判断障碍物的距离;利用蚁群算法对管道机器人行驶路径进行规划,有效解决了管道机器人障碍物识别与规避的问题。研究结果表明:该方法能够实现管道机器人障碍物距离判断以及避障过程的路径规划功能,符合管道检测的实用要求,具有较高的实际应用价值。To ensure the safe operation of pipelines,it is essential to employ effective detection methods and means to identify and assess defects and damages in the pipelines.Currently,pipeline robots are the most efficient means for pipeline inspection;however,during the inspection process,various obstacles(defects)can impact the efficiency of detection.In light of this,based on a thorough analysis of the motion characteristics of pipeline robots,this paper proposes an obstacle avoidance strategy for pipeline robots using ant colony algorithm and binocular vision.Binocular vision is utilized for rapid three-dimensional reconstruction of obstacles,enabling effective determination of obstacle distances.The ant colony algorithm is employed to plan the trajectory of the pipeline robot's movement.This strategy effectively addresses the challenges of obstacle recognition and avoidance for pipeline robots.Research results demonstrate that this approach can achieve obstacle distance determination and path planning for obstacle avoidance in pipeline robot operations.It complies with practical requirements for pipeline inspection,showcasing significant practical application value.

关 键 词：管道 机器人 避障 蚁群算法 双目视觉 

分 类 号：TP242.6[自动化与计算机技术—检测技术与自动化装置]